Services

AI automation, prompt engineering and AI coding services.

Service areas for practical business systems: automation workflows, prompt systems, RAG knowledge bases, agents, integrations and MVPs.

AI Automation

Design and implementation of workflow automation systems using n8n, APIs, webhooks, scheduled jobs and AI nodes.

Deliverables

  • workflow map
  • n8n implementation
  • API connections
  • error handling

Typical stack

n8n · OpenAI · Claude · REST APIs · webhooks

n8nAPIswebhooksschedulingerror handling

Prompt Engineering

System prompts, assistant instructions, retrieval-first behavior, agent workflows and reusable prompt patterns for business use cases.

Deliverables

  • system prompt
  • prompt library
  • evaluation checklist
  • hallucination controls

Typical stack

OpenAI · Claude · Codex workflows · RAG · evaluations

system promptsRAGguardrailsstructured outputs

RAG Knowledge Bases

Retrieval systems over internal documents, FAQs, PDFs, databases and operational knowledge.

Deliverables

  • content ingestion
  • chunking strategy
  • embeddings
  • vector search

Typical stack

PostgreSQL · pgvector · OpenAI · document parsing

ingestionchunkingembeddingsvector searchgrounding

Vibe Coding & MVPs

AI-assisted development workflows for prototypes, landing pages, internal tools and MVPs with fast iteration.

Deliverables

  • prototype
  • UI implementation
  • prompt-to-code workflow
  • refactoring

Typical stack

Next.js · React · TypeScript · Tailwind CSS · Codex

prompt-to-codeMVPsinternal toolscode review

CRM / ERP Integrations

Connecting AI workflows with CRM, ERP, messaging platforms and operational systems.

Deliverables

  • integration plan
  • API mapping
  • automation flow
  • status sync

Typical stack

Bitrix24 · amoCRM · Acumatica · Telegram · Chatwoot

CRMERPTelegramWhatsAppstatus sync

AI Agents

Task-oriented AI agents with access to tools, knowledge bases, APIs and controlled execution paths.

Deliverables

  • agent architecture
  • tool definitions
  • memory/retrieval design
  • fail-safe logic

Typical stack

OpenAI · Claude · tool calling · RAG · APIs

tool usageretrievalconstraintsQA scenarios

Delivery process

A small process keeps the engagement measurable without turning it into a heavy consulting project.

  1. 01Map the workflow. Understand the business workflow, tools, data sources and constraints.
  2. 02Design the AI layer. Decide where AI is useful: classification, retrieval, generation, routing, extraction or decision support.
  3. 03Build the system. Implement workflows, prompts, integrations, vector search, UI and logging.
  4. 04Test against reality. Run edge cases, broken inputs, missing data and hallucination scenarios.
  5. 05Deploy and iterate. Ship, monitor, document and improve.
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